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A Two-Stage U-Net to Estimate the Cultivated Area of Plantations

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Image Analysis and Processing – ICIAP 2022 (ICIAP 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13231))

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Abstract

In order to reduce tax evasion in agribusiness, it is possible to estimate the production of crops through the monitoring and analysis of satellite images and compare with the values declared by the taxpayer. For this, deep learning techniques can be applied to satellite images to segment the cultivated area of plantations, and the segmented area can be used to estimate crop yields. As an initial step, this work aims to analyze the satellite images of plantations to estimate the cultivated area of plantations using semantic segmentation. For this, we created a dataset for planting areas data, and we proposed network architecture for image segmentation, a two-stage U-net. The proposed methodology returned average IoU results above 80% in both stages.

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Acknowledgements

The authors thank the National Council for Scientific and Technological Development (CNPq), This work was supported by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) - Finance Code 001 and the Foundation for Research and Scientific and Technological Development of the State of Maranhão (FAPEMA) for the financial support for the development of this work.

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Authors and Affiliations

  1. Universidade Federal do Maranhão - UFMA, 322, São Luís, MA, 65.086-110, Brazil

    Walysson Carlos dos Santos Oliveira, Geraldo Braz Junior, Daniel Lima Gomes Junior, Anselmo Cardoso de Paiva & Joao Dallyson Sousa de Almeida

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  1. Walysson Carlos dos Santos Oliveira
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  2. Geraldo Braz Junior
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  3. Daniel Lima Gomes Junior
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  4. Anselmo Cardoso de Paiva
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  5. Joao Dallyson Sousa de Almeida
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Corresponding author

Correspondence to Walysson Carlos dos Santos Oliveira .

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Editors and Affiliations

  1. Boston University, Boston, MA, USA

    Stan Sclaroff

  2. National Research Council, Lecce, Italy

    Cosimo Distante

  3. National Research Council, Lecce, Italy

    Marco Leo

  4. University of Catania, Catania, Italy

    Giovanni M. Farinella

  5. Technische Universität München, Garching, Germany

    Federico Tombari

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dos Santos Oliveira, W.C., Braz Junior, G., Lima Gomes Junior, D., Cardoso de Paiva, A., Sousa de Almeida, J.D. (2022). A Two-Stage U-Net to Estimate the Cultivated Area of Plantations. In: Sclaroff, S., Distante, C., Leo, M., Farinella, G.M., Tombari, F. (eds) Image Analysis and Processing – ICIAP 2022. ICIAP 2022. Lecture Notes in Computer Science, vol 13231. Springer, Cham. https://doi.org/10.1007/978-3-031-06427-2_29

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  • DOI: https://doi.org/10.1007/978-3-031-06427-2_29

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-06426-5

  • Online ISBN: 978-3-031-06427-2

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